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Self-reported symptoms and healthcare seeking in the general population -exploring “The Symptom Iceberg”

  • Sandra Elnegaard1Email author,
  • Rikke Sand Andersen2,
  • Anette Fischer Pedersen2,
  • Pia Veldt Larsen1,
  • Jens Søndergaard1,
  • Sanne Rasmussen1,
  • Kirubakaran Balasubramaniam1,
  • Rikke Pilsgaard Svendsen1,
  • Peter Vedsted2 and
  • Dorte Ejg Jarbøl1
BMC Public Health201515:685

https://doi.org/10.1186/s12889-015-2034-5

Received: 6 October 2014

Accepted: 7 July 2015

Published: 21 July 2015

Abstract

Background

Research has illustrated that the decision-making process regarding healthcare seeking for symptoms is complex and associated with a variety of factors, including gender differences. Enhanced understanding of the frequency of symptoms and the healthcare seeking behaviour in the general population may increase our knowledge of this complex field.

The primary objective of this study was to estimate the prevalence of self-reported symptoms and the proportion of individuals reporting GP contact, in a large Danish nationwide cohort. A secondary objective was to explore gender differences in GP contacts in response to experiencing one of the 44 predefined symptoms.

Methods

A Danish nationwide cohort study including a random sample of 100,000 individuals, representative of the adult Danish population aged 20 years or above. A web-based questionnaire survey formed the basis of this study. A total of 44 different symptoms covering a wide area of alarm symptoms and non-specific frequently occurring symptoms were selected based on extensive literature search. Further, items regarding contact to the GP were included. Data on socioeconomic factors were obtained from Statistics Denmark.

Results

A total of 49,706 subjects completed the questionnaire. Prevalence estimates of symptoms varied from 49.4 % (24,537) reporting tiredness to 0.11 % (54) reporting blood in vomit. The mean number of reported symptoms was 5.4 (men 4.8; women 6.0).

The proportion of contact to the GP with at least one symptom was 37 %. The largest proportion of GP contacts was seen for individuals reporting blood in the urine (73.2 %), whereas only 11.4 % of individuals with increase in waist circumference reported GP contact. For almost 2/3 of the symptoms reported, no gender differences were found concerning the proportion leading to GP contacts.

Conclusion

Prevalence of symptoms and GP contacts are common in this overview of 44 different self-reported symptoms. For almost 2/3 of the reported symptoms no gender differences were found concerning the proportion leading to GP contacts. An enhanced understanding of healthcare seeking decisions may assist healthcare professionals in identifying patients who are at risk of postponing contact to the GP and may help development of health campaigns targeting these individuals.

Keywords

General practice Symptom experience Questionnaire Healthcare seeking Gender Symptom iceberg Population based Denmark

Background

Knowledge about symptoms and healthcare seeking decisions provides an arena for understanding the interface between the healthcare system and the population. Since the 1960s we have witnessed a series of studies exploring the prevalence of symptoms and the proportion of healthcare seeking [15]. This phenomenon was identified as “The Symptom Iceberg” for the first time in 1963 by JM Last [1] and operationally defined by Hannay in 1979 [6]. The phenomenon depicts two parts – the “submerged part” encompassing the majority of symptom experiences, which are not brought to the attention of a general practitioner (GP), and the “surfaced part” symbolising the proportion of symptoms, which are presented to the GP.

The prevalence of self-reported symptoms varies in the existing literature. Two recent studies estimated the prevalence of symptoms, but in two different settings: a community-based survey among people with musculoskeletal complaints explored the prevalence of 25 different symptoms [7] and a population based study drawn from general practices in the UK explored the prevalence of 23 different symptoms [8]. They found an average number of symptoms experienced during the preceding 2 weeks of 3.7 and 6.0, respectively [7, 8]. Further, research has found a wide range in the proportion who contacted the GP in response to a symptom, from 5–25 % [714].

Studies have illustrated that the decision process regarding healthcare seeking for a symptom is complex and depends on a variety of different factors, which possibly differ among men and women [15]. It has been argued that women are socialised to pay more attention to their bodies and tend to seek more medical advice than men [16]. However, the greater tendency to consult amongst women is not consistent in the literature [15, 17].

From a public health perspective people’s decision about healthcare seeking is important with regard to improvements in risk profiling and diagnostics, such as e.g. cancer diagnostics. Symptoms potentially indicative of serious disease should preferably lead to healthcare seeking, while other symptoms should not. However, it is a challenge that most symptoms have low positive predictive values for serious disease [18]. Further, the awareness that some symptoms may be a sign of serious disease may differ among different groups in the population [19]. This has to be systematically explored in large-scale studies in a general population. An enhanced understanding of the size of the pool of symptoms and subsequent consequences in the population may improve policy interventions targeting healthcare seeking, e.g. systematic patient delays. Investigating a wide range of self-reported symptoms and the subsequent healthcare seeking decision is therefore important.

The primary objective of this study was to estimate the prevalence of self-reported symptoms and the proportion of individuals reporting GP contact, in a large Danish nationwide cohort. A secondary objective was to explore gender differences in GP contacts in response to experiencing one of the 44 predefined symptoms.

Methods

Study design

This study was part of a Danish nationwide cohort comprising a random sample of 100,000 individuals, representative of the adult Danish population aged 20 years or above. The overall aim of the cohort study was to estimate the prevalence of symptoms among individuals in the general population, the individuals’ interpretation of symptoms, related factors influencing the decision to contact the GP and their healthcare-seeking behaviour. Further, the cohort will be followed-up using registers on health care utilization and hospital admissions to explore the predictive values of the symptoms for various diseases.

Baseline data presented in this paper were collected in a web-based survey. The data collection was conducted from June to December 2012, thereby excluding the months where the flu activity in Denmark normally peaks.

Subjects and sampling

All Danish citizens are registered with a unique personal identification number in the Danish Civil Registration System (CRS), which contains information on any Danish resident’s date of birth, gender, migration, etc. The CRS enables accurate linkage between all national registers [20]. The sample for this study was randomly selected using the CRS and was invited to participate in the survey. Each individual received a postal letter explaining the purpose of the study. In the letter a unique 12-digit login for a secure webpage was included. This provided access to a comprehensive web-based questionnaire [21].

The initial invitation letter was followed by a reminder to non-respondents after two weeks. After an additional two weeks the non-respondents were contacted by telephone and encouraged to participate. In order to prevent the exclusion of people with no access to a computer, tablet or smartphone, the participants were offered the opportunity to respond to the survey in a telephone interview. Information on severe illness and subjects who had moved abroad was occasionally provided by family or relatives in the reminder procedure [21].

Questionnaire

A comprehensive questionnaire including 44 different symptoms covering a wide area of clinically relevant predefined symptoms was developed. For representativeness of symptoms that from a medical perspective are defined as indicating a serious disease, we selected a number of alarm symptoms of cancer covering the following areas: lung, gastrointestinal, gynaecological, and urogenital cancer. These items were selected based on a review of literature, national and international cancer referral guidelines and descriptions of cancer pathways [2224]. In addition, we included a number of frequently occurring symptoms, which are often presented to the GP, e.g. back pain, headache and tiredness. Items regarding each specific symptom were phrased: “Have you experienced any of the following bodily sensations, symptoms or discomfort within the past four weeks?” With regard to GP contact, the question was worded for each selected symptom: “Have you contacted your general practitioner concerning the symptom(s) you have experienced within the past four weeks, through appointment, by telephone or e-mail?”

The questionnaire was pilot- and field-tested and adjusted in light of the results from these. The methodological framework for developing the questionnaire is described in details elsewhere [21].

Responder analysis

In order to compare the study sample, respondents and non-respondents, data on socioeconomic and demographic factors were collected from Statistics Denmark [25]. For each individual we obtained information on education, income, labour market affiliation, cohabitation status, ethnicity and average number of contacts to the GP. Information was retrieved for the year 2011, i.e. the year preceding the questionnaire study. Education was categorised according to the length of the highest attained educational level: low (<10 years (primary and lower secondary school)); middle (10–12 years (vocational education and upper secondary school)); and high (>12 years (short-, medium- and long-term higher education)). This categorisation was selected to reflect the organisation of the Danish educational system [26]. Equivalence weighted disposable income was categorised as low income (1st quartile), middle income (2nd and 3rd quartile), and high income (4th quartile). Labour market affiliation was categorised into three groups: (i) working, (ii) pensioners and (iii) out of the workforce. Cohabitation status was categorised into: cohabiting/married or single. Ethnicity was categorised into three groups: persons with Danish origin, immigrants, and descendants of immigrants. The total number of contacts to the GP in 2011 was obtained from the National Health Service Register [25].

Statistical analysis

The following socioeconomic and demographic characteristics of the study sample, respondents and non-respondents were described: sex, age, education, income, labour market affiliation, cohabitation status, ethnicity and average contacts to GP the preceding year. Chi-square tests were used to test for differences between characteristics of respondents and non-respondents.

Prevalence estimates of each reported symptom and the proportion of individuals with contact to the GP were calculated with 95 % confidence intervals based on the binominal distribution. The reported symptoms were ranked according to their frequency. Respondents answering ”not relevant for me” were excluded from the analysis and the answers “do not wish to answer” which accounted for less than 5 %, was considered as missing and not included in the analyses. In order to explore the pattern of “The Symptom Iceberg” for each gender, the prevalence of symptom experiences and proportion of contacts to the GP were stratified on gender. We tested whether the prevalence estimates differed between genders using chi-squared tests. Contacts to GP were ranked separately for men and women, according to the proportion contacting the GP in response to experiencing a symptom.

A histogram of the number of reported symptoms by the participants was constructed for the full sample as well as for men and women separately. For each number of symptoms, the proportion contacting the GP with at least one of the symptoms was indicated. All data analyses were conducted using StataIC 13©.

Ethical approval

The Regional Scientific Ethics Committee for Southern Denmark evaluated the project and concluded that no further approval was necessary due to Danish legislation. The participants in the study were clearly informed that there would be no clinical follow-up, and that they should contact their own GP in case of concern or worry. The project was approved by the Danish Data Protection Agency (journal no. 2011-41-6651).

Results and discussion

Of the 100,000 randomly selected subjects, 4,474 (4.7 %) were not eligible because they had either died, were suffering from severe illnesses (including dementia), had language problems, had moved abroad or could not be reached due to unknown address. Of the 95,253 (95.3 %) eligible subjects, 49,706 subjects completed the questionnaire, yielding a response rate of 52.2 %. Some 1,208 (2.4 %) completed the questionnaire by telephone. Of all non-respondents, 26,008 (57.1 %) indicated that they did not wish to participate in the study, whereas for the remaining 19,539 (42.9 %) no contact was achieved during the reminder procedure (Fig. 1). The electronic format of the questionnaire enabled a leap structure, so the respondents were directed through the questionnaire according to their previously given answers, skipping irrelevant questions. Further, the structure ensured that respondents were required to answer each question in order to continue to the next. Less than 5 % of the respondents did not complete the questionnaire.
Fig. 1

Study cohort

Table 1 shows socioeconomic and demographic characteristics of the total study sample, respondents and non-respondents, respectively. The median age of the study sample was 51 years (IQR 38–65). Median age of respondents was slightly higher than non-respondents; 52 years (IQR 40–64) compared to 50 years (IQR 36–66), respectively. The respondents were fairly representative of the study sample. However, more respondents were females, married/living together, had a high educational and income level and were attached to the labour market. Differences between respondents, non-respondents and the study sample according to descriptive characteristics are shown in Table 1.
Table 1

Descriptive characteristics of the total sample, respondents and non-respondents in the survey (N = 100 000)

 

Total sample

Respondents

Non-respondents

    
 

N

%

n

%

n

%

P-value*

Sex

       

Male

48 910

48.9

23 240

46.8

23 407

51.4

<0.001

Female

51 090

51.1

26 466

53.2

22 140

48.6

Age

       

2039

27 706

27.7

12 251

24.6

15 455

30.7

<0.001

4059

37 106

37.1

20 305

40.9

16 801

33.4

6079

28 868

28.9

15 748

31.7

13 120

26.1

80-

6 320

6.3

1 402

2.8

4 918

9.8

Marital statusa

       

Single

31 140

32.8

12 475

25.1

18 665

41.2

<0.001

Married/living together

63 807

67.2

37 140

74.9

26 667

58.8

Educational levela

       

Low

24 770

27.2

9 540

19.7

15 230

35.6

<0.001

Medium

40 659

44.6

22 155

45.8

18 504

43.3

High

25 752

28.2

16 724

34.5

9 028

21.1

Income levela

       

Low

22 440

23.6

8 072

16.3

14 368

31.7

<0.001

Medium

48 126

50.7

25 712

41.8

22 414

49.4

High

24 382

25.7

24 382

31.9

8 551

18.9

Employment statusa

       

Workning

59 961

63.1

33 961

68.4

26 000

57.3

<0.001

Pensioners

23 193

24.4

11 294

22.7

11 899

26.2

Out of workforce

11 911

12.5

4 410

8.9

7 501

16.5

Ethnic groupsa

       

Danish

86 248

90.8

46 543

93.8

39 705

87.6

<0.001

Immigrants

8 038

8.5

2 858

5.8

5 180

11.4

Descendants of Immigrants

661

0.7

214

0.4

447

1.0

GP contactsa

       

Average contacts to GP in 2011

8.1

 

7.6

 

8.5

 

<0.001

aTotal numbers for each group may not add up to full sample, 5 to 9 % missing data from Statistics Denmark

*Differences between respondents and non-respondents according to descriptive characteristics were tested using chi-square tests

Prevalence estimates of self-reported symptoms in the preceding four weeks and the proportions of individuals with report of contact to the GP are listed in Table 2. Prevalence estimates of symptoms varied from 49.4 % (24,537) reporting tiredness to 0.11 % (54) reporting blood in vomit. The symptoms are ranked by frequency. The largest proportion of GP contacts was observed for individuals reporting blood in the urine 73.2 %, whereas 11.4 % of individuals with increase in waist circumference reported contact to the GP (Table 2).
Table 2

The Symptom Iceberg – Prevalence of self-reported symptoms in the previous 4 weeks and the proportion of GP contacts. Ranked from 1 to 44 according to proportion of symptoms in the study population

 

Proportion with symptoms

Proportion with GP contacts

 

N

%

[95 % CI]

Rank

N

%

[95 % CI]

Tiredness

24 537

49.8

[49.4–50.3]

1

4 907

20.2

[19.7–20.7]

Night-time urination

23 935

48.7

[48.2–49.1]

2

3 024

12.8

[12.3–13.2]

Lack of energy

18 472

37.5

[37.1–37.9]

3

3 599

19.7

[19.1–20.3]

Headache

17 978

36.5

[36.1–37.0]

4

3 159

17.7

[17.2–18.3]

Back pain

15 925

32.3

[31.9–32.8]

5

5 490

34.9

[34.1–35.6]

Abdominal bloating

14 712

29.8

[29.4–30.2]

6

1 864

12.9

[12.3–13.4]

Memory problems

9 824

19.9

[19.6–20.3]

7

1 771

18.3

[17.6–19.1]

Abdominal pain

9 765

19.6

[19.4–20.1]

8

2 659

27.8

[26.9–28.7]

Erectile dysfunctiona

4 289

19.3

[18.8–19.8]

9

1 362

32.1

[30.7–33.5]

Coughing

8 804

17.9

[17.5–18.2]

10

2 120

24.4

[23.5–25.3]

Concentration problems

8 662

17.6

[17.2–17.9]

11

1 742

20.4

[19.6–21.3]

Change in stool texture

8 543

17.3

[17.0–17.6]

12

1 260

15.0

[14.3–15.8]

Dizziness

7 889

16.0

[15-7-16-3]

13

2 407

30.9

[29.9–32.0]

Pelvic paina

3 963

15.4

[14.9–15.8]

14

1 008

25.8

[24.4–27.2]

Feeling unwell

7 411

15.0

[14.7–15.4]

15

2 065

28.3

[27.3–29.3]

Constipation

7 231

14.7

[14.3–15.0]

16

970

13.6

[12.9–14.5]

Increase in waist circumference

6 548

13.3

[13.0–13.7]

17

733

11.4

[10.6–12.2]

Change in stool frequency

6 466

13.1

[12.8–13.4]

18

1 009

15.9

[15.0–16.8]

Diarrhoea

6 385

12.9

[12.7–13.2]

19

1 057

16.8

[15.9–17.7]

Nausea

6 256

12.6

[12.3–12.9]

20

1 264

20.6

[19.6–21.6]

Swollen legs

6 056

12.3

[12.0–12.6]

21

2 224

37.2

[36.0–38.5]

Difficulty in emptying the bladder

5 731

11.6

[11.4–11.9]

22

1 534

27.1

[26.0–28.3]

Frequent urination

5 234

10.6

[10.4–10.9]

23

1 362

26.5

[25.3–27.7]

Pelvic pain during intercoursea

2 091

10.2

[9.8–10.6]

24

552

26.6

[24.8–28.6]

Stress incontinence

4 797

9.8

[9.5–10.0]

25

852

18.0

[16.8–19.1]

Shortness of breath

3 960

8.0

[7.8–8.3]

26

1 936

49.7

[48.1–51.2]

Hoarseness

3 782

7.7

[7.4–7.9]

27

698

18.7

[17.5–20.0]

Urge incontinence

3 080

6.3

[6.0–6.5]

28

790

26.1

[24.5–27.6]

Loss of appetite

3 079

6.3

[6.0–6.5]

29

586

19.4

[18.1–20.9]

Blood in stool/rectal bleeding

2 285

4.6

[4.4–4.8]

30

758

33.7

[31.8–35.7]

Fever

1 952

4.0

[3.8–4.1]

31

517

26.8

[24.9–28.8]

Difficulty swallowing

1 727

3.5

[3.3–3.7]

32

586

34.9

[32.6–37.2]

Weight loss

1 490

3.0

[2.9–3.2]

33

363

25.1

[23.0–27.4]

Vaginal bleeding after intercoursea

612

3.0

[2.8–3.2]

34

187

30.9

[27.2–34.7]

Incontinence without stress/urge

1 158

2.3

[2.2–2.5]

35

383

33.8

[31.1–36.6]

Postmenopausal bleedinga

370

2.3

[2.1–2.5]

36

118

33.1

[28.2–38.2]

Pain/burning when urinating

1 046

2.1

[2.0–2.3]

37

489

47.8

[44.7–50.8]

Lump/swollen lymph nodes

811

1.6

[1.5–1.8]

38

332

41.5

[38.1–45.0]

Black stool

779

1.6

[1.5–1.7]

39

132

17.3

[14.8–20.2]

Repeated vomiting

643

1.3

[1.2–1.4]

40

208

33.6

[30.0–37.4]

Blood in urine

284

0.6

[0.5–0.7]

41

202

73.2

[67.6–78.1]

Blood in semena

94

0.4

[0.3–0.5]

42

45

48.9

[38.7–59.2]

Coughing up blood

62

0.1

[0.1–0.2]

43

29

47.5

[35.1–60.3]

Blood in vomit

54

0.1

[0.1–0.1]

44

17

37.0

[23.9–52.2]

a Gender specific symptoms

About 9 out of 10 respondents reported at least one symptom within the preceding four weeks. The mean number of reported symptoms was 5.4 (men: 4.8; women: 6.0, p < 0.001). The number of symptoms reported ranged from 0 to 39. Figure 2, illustrates the proportion who reported the given number of symptoms and the proportion with the given number of symptoms who contacted the GP with at least one symptom. Women were most likely to have reported four symptoms within the preceding four weeks, while men were most likely to have reported two symptoms. The proportion of symptoms leading to GP contacts increased with increasing number of symptoms experienced. This was similar for both men and women (Fig. 2). The gender-specific prevalences of reported symptoms and proportions of GP contact are listed in Table 3.
Fig. 2

The graphs show the proportion who experienced the given number of symptoms (light blue bar) and the proportion with the given number of symptoms who contacted the GP with at least one symptom (dark blue bar). The red line and the right y-axis refer to the linear relationship between the number of symptoms and the proportion of GP contacts among individuals with the given number of symptoms. The graph is shown for the total sample and for men and women separately

Table 3

Prevalence of symptoms and GP contacts, stratified on gender. Proportions of GP-contacts were ranked from 1 to 42 according to frequency

 

Proportion with symptoms

Proportion with GP contacts

 

Gender

n

%

n

%

[95 % CI]

Rank

p-value*

Tiredness

Men

10 642

45.8

1 923

18.3

[17.5–19.0]

28

<0.001

Women

13 895

52.5

2 984

21.7

[21.0–22.4]

26

Night-time urination

Men

11 424

49.2

1 928

17.0

[16.3–17.7]

31

<0.001

Women

12 511

47.3

1 096

8.9

[8.4–9.4]

42

Lack of energy

Men

8 215

35.3

1 437

17.7

[16.8–18.5]

29

<0.001

Women

10 257

38.8

2 162

21.4

[20.6–22.2]

27

Headache

Men

6 675

28.7

1 016

15.3

[14.5–16.2]

36

<0.001

Women

11 303

42.7

2 143

19.2

[18.4–19.9]

34

Back pain

Men

7 067

30.4

2 468

35.2

[34.1–36.3]

10

0.437

Women

8 858

33.5

3 022

34.6

[33.6–35.6]

8

Abdominal bloating

Men

5 073

21.8

674

13.5

[21.5–14.5]

38

0.101

Women

9 639

36.4

1 190

12.5

[11.9–13.2]

40

Memory problems

Men

4 177

18.0

691

16.8

[15.7–18.0]

32

0.001

Women

5 647

21.3

1 080

19.5

[18.4–20.5]

33

Abdominal pain

Men

3 273

14.1

1 002

31.3

[29.7–32.9]

16

<0.001

Women

6 492

24.5

1 657

26.0

[25.0–27.2]

19

Coughing

Men

4 212

18.1

953

22.9

[21.6–24.2]

24

0.002

Women

4 592

17.4

1 167

25.7

[24.5–27.0]

21

Concentration problems

Men

3 566

15.3

687

19.5

[18.2–20.9]

26

0.089

Women

5 096

19.3

1 055

21.0

[19.9–22.2]

28

Change in stool texture

Men

3 858

16.6

542

14.3

[13.2–15.4]

37

0.083

Women

4 685

17.7

718

15.6

[14.6–16.7]

37

Dizziness

Men

3 101

13.3

961

31.3

[29.7–33.0]

15

0.557

Women

4 788

18.1

1 446

30.7

[29.4–32.0]

14

Feeling unwell

Men

3 042

13.1

831

27.7

[26.1–29.3]

19

0.337

Women

4 369

16.5

1 234

28.7

[27.4–30.1]

15

Constipation

Men

2 422

10.4

317

13.3

[12.0–14.7]

39

0.542

Women

4 809

18.2

653

13.8

[12.9–14.8]

39

Increase in waist circumference

Men

2 266

9.7

217

9.7

[8.5–11.0]

40

0.002

Women

4 282

16.2

516

12.3

[11.3–13.3]

41

Change in stool frequency

Men

2 757

11.9

444

16.5

[15.1–17.9]

33

0.308

Women

3 709

14.0

565

15.5

[14.4–16.7]

38

Diarrhoea

Men

2 946

12.7

476

16.4

[15.1–17.8]

34

0.436

Women

3 439

13.0

581

17.1

[15.9–18.5]

35

Nausea

Men

1 887

8.1

391

21.1

[19.2–23.0]

25

0.522

Women

4 369

16.5

873

20.4

[19.2–21.6]

29

Swollen legs

Men

1 953

8.4

870

45.1

[42.8–47.3]

4

<0.001

Women

4 103

15.5

1 354

33.5

[32.1–35.0]

10

Difficulty in emptying the bladder

Men

3 365

14.5

995

29.9

[28.4–31.5]

17

<0.001

Women

2 366

8.9

539

23.1

[21.4–24–9]

25

Frequent urination

Men

2 597

11.2

738

28.8

[27.0–30.6]

18

<0.001

Women

2 637

10.0

624

24.2

[22.5–25.9]

24

Stress incontinence

Men

256

1.1

90

35.7

[29.8–42.0]

9

<0.001

Women

4 541

17.2

762

17.0

[15.9–18.1]

36

Erectile dysfunctiona

Men

4 289

18.5

1 362

32.1

[30.7–33.5]

14

-

-

-

-

-

-

-

-

Pelvic paina

-

-

-

-

-

-

-

-

Women

3 963

15.0

1 008

25.8

[24.4–27.2]

20

Shortness of breath

Men

1 912

8.3

960

50.9

[48.6–53.2]

2

0.139

Women

2 048

7.7

976

48.5

[46.3–50.7]

4

Hoarseness

Men

1 677

7.2

293

17.7

[15.9–19.6]

30

0.147

Women

2 105

8.0

405

19.6

[17.9–21.3]

32

Urge incontinence

Men

1 184

5.1

322

27.7

[25.2–30.4]

20

0.102

Women

1 896

7.2

468

25.0

[23.1–27.1]

23

Loss of appetite

Men

1 359

5.8

256

19.2

[17.1–21.4]

27

0.767

Women

1 720

6.5

330

19.6

[17.7–21.6]

31

Blood in stool/rectal bleeding

Men

1 103

4.7

366

33.7

[30.9–36.6]

12

0.963

Women

1 182

4.5

392

33.8

[31.1–36.6]

9

Pelvic pain during intercoursea

-

-

-

-

-

-

-

-

Women

2 091

7.9

552

26.6

[24.7–28.6]

18

Fever

Men

841

3.6

211

25.3

[22.4–28.4]

22

0.18

Women

1 111

4.2

306

28.0

[25.4–30.8]

16

Difficulty swallowing

Men

781

3.4

254

33.2

[29.9–36.7]

13

0.205

Women

946

3.6

332

36.2

[33.1–39.4]

7

Weight loss

Men

768

3.3

185

24.8

[21.7–28.1]

23

0.758

Women

722

2.7

178

25.5

[22.3–28.9]

22

Incontinence without stress/urge

Men

328

1.4

111

34.7

[29.5–40.2]

11

0.703

Women

830

3.1

272

33.5

[30.3–36.9]

11

Pain/burning when urinating

Men

384

1.5

156

41.4

[36.4–46.5]

6

0.002

Women

662

2.5

333

51.5

[47.5–55.4]

3

Lump/swollen lymph nodes

Men

268

1.2

109

40.8

[34.9–47.0]

7

0.784

Women

543

2.1

223

41.8

[37.6–46.2]

5

Black stool

Men

451

1.9

68

15.4

[12.1–19.1]

35

0.093

Women

328

1.2

64

20.1

[15.8–24.9]

30

Repeated vomiting

Men

243

1.0

62

26.8

[21.2–33.0]

21

0.006

Women

400

1.5

146

37.6

[32.8–42.7]

6

Vaginal bleeding after intercoursea

-

-

-

-

-

-

-

-

Women

612

2.3

187

30.9

[27.2–34.7]

13

Postmenopausal bleedinga

-

-

-

-

-

-

-

-

Women

370

1.4

118

33.1

[28.2–38.2]

12

Blood in urine

Men

125

0.5

86

69.9

[61.0–77.9]

1

0.272

Women

159

0.6

116

75.8

[68.2–82.4]

1

Blood in semena

Men

94

0.4

45

48.9

[38.3–59.6]

3

-

-

-

-

-

-

-

-

Coughing up blood

Men

42

0.2

18

43.9

[28.5–60.3]

5

0.415

Women

20

0.1

11

55.0

[31.5–76.9]

2

Blood in vomit

Men

32

0.1

11

39.3

[21.5–59.4]

8

0.683

Women

22

0.1

6

33.3

[13.3–59.0]

17

*Differences in GP-contacts with a symptom between genders were tested using chi-square tests

aTotal numbers for each gender specific symptoms may not add up to full sample, due to the answer “do not wish to answer” was considered as missing (1.14.6 %) in the analyses

In total, 37 % contacted the GP with at least one symptom. For almost 2/3 of the reported symptoms, no statistically significant differences in reporting contacts to GP were found between the genders. However, women more often than men contacted the GP with repeated vomiting, coughing, tiredness and lack of energy, whereas men more often than women contacted the GP with stress incontinence, difficulties emptying the bladder, frequent urination, night-time urination and swollen legs (Table 3).

Summary of main findings

This population based nationwide study demonstrated that symptoms were common; about 9 out of 10 individuals reported at least one symptom within the preceding four weeks. On average, women reported more symptoms than men; however, for some symptom the prevalence was higher for men. The majority of reported symptoms were not presented to the GP; the proportion of respondents contacting the GP with at least one symptom was 37 %. For 2/3 of the reported symptoms no gender differences in GP contacts were found.

Strengths and limitations of the study

This study is a large nationwide population based study, including 100,000 individuals randomly selected from the Danish CRS register, representative of the adult Danish population aged 20 or above. To our knowledge such a large-scale population based study, investigating a wide range of self-reported symptoms covering specific and nonspecific cancer alarm symptoms as well as frequently occurring symptoms, has not previously been conducted.

The response rate of 52.2 % was comparable or even higher compared to previous surveys measuring symptom prevalences in the general population [27]. However, it is unknown whether individuals who had experienced symptoms might have been less or more inclined to participate in the study.

Information on symptoms and healthcare seeking decisions was self-reported, and respondents were asked to recall which of the 44 symptoms they had experienced in the preceding four weeks, and whether they at any time had contacted the GP with the symptoms they had experienced within the past four weeks. However, recall bias cannot be ruled out in questionnaire studies [28]. Some may misplace previous experiences of symptoms into the specified timeframe due to the severity of the symptoms or because they had contacted the GP about them [29]. Others may have forgotten about the experience of symptoms or GP contact because the symptom turned out to be inconsequential, or simply due to memory decay [30]. A higher proportion of individuals reporting GP contact with a symptom was found compared to other studies which might be explained by the unspecified timeframe for GP contact. In particular, this may be the case for the more frequently occurring symptoms such as back pain.

The web-based questionnaire was not available in a paper version, which might have prevented some individuals from participating in the study, especially the elderly. However, this possible selection bias was sought minimised by offering individuals without a computer the possibility to complete the survey by telephone interview.

Symptoms and measurement – The Symptom Iceberg

When measuring symptoms, it is essential to define what a symptom is and how to measure it. As stated by Kroenke ’symptoms research is a fertile field’ [31], and we need to be more explicit about the way we conceptualise and measure symptoms. In this study we consider symptoms to be subjective interpretations of sensations and bodily changes, which are not necessarily an indication of an underlying disease.

Since no gold standard for measuring symptoms exits, studies on the prevalence of reported symptoms use different methodological approaches, which complicate comparison of the results between studies. However, despite the methodological differences, our results regarding the most frequently experienced symptoms are broadly consistent with previous symptom research [6, 8, 32]. This study focuses on individual reported symptoms, the total number of reported symptoms and corresponding contacts to the GP. Future studies might address how specific clusters of symptoms may affect the proportion of GP contacts.

Gender differences

Some studies on symptoms and GP contacts suggest that men are less likely than women to report symptoms and to contact the GP [33]. However, other studies suggest that once a symptom is experienced and recognised, there are no gender differences in the tendency to contact the GP [5, 34, 35]. The results of this study show that for almost 2/3 of the reported symptoms, no statistically significant gender differences in reporting contact to GP were found.

GP contacts - The “surfaced” part of The Symptom Iceberg

We found that 37 % contacted the GP with at least one of the symptoms experienced within the preceding four weeks. This proportion is relatively high compared to existing literature [5, 1113, 27]. The original concept about “The Symptom Iceberg” was that approximately 10 % of all symptoms resulted in contact to the GP [36]. Our proportion of self-reported GP contacts might be higher as a result of the wording of the questions, different methodological approaches, or because of the changed cultural differences in the arena where people and GPs meet. Current medical practice is characterised by a focus on risk reduction and early detection of illness, which combined with developments in biomedical knowledge and diagnostic technologies has expanded “the pool of potential symptoms” [37]. Thus, more bodily changes, feelings or sensations may be designated as potential signs of disease. It is therefore to be expected that the pool of self-reported symptoms increases, and we may see a higher frequency of healthcare seeking. However, this should be further explored.

The decision on whether to contact a GP is based on a complex mix of physical, psychological and social factors [38]. The same symptom may by some people be regarded as harmless, while others may consider it as being too serious to ignore. The persistence of a symptom may also influence the interpretation of the symptom. These considerations or interpretations of the symptom will affect the decision on whether or not to contact the GP. The key issue seems not always to be the symptom itself.

Early diagnosis and prompt treatment are generally presumed to be a key to a better prognosis of most illnesses. An enhanced understanding of healthcare-seeking behaviours may assist health care professionals in identifying patients who are at risk of postponing contact to the GP and may help development of health campaigns targeting these individuals.

The literature indicates that multiple factors may affect peoples’ decision to seek healthcare. In this study we focused on prevalence and gender differences with regard to reporting of symptoms and contact to the GP. Future studies should explore other possible factors, which might trigger the individual to contact the GP, including age, characteristics of the symptoms and sociocultural factors such as use of social network in relation to a symptom.

Conclusions

This study provides a comprehensive overview of the prevalences of 44 different self-reported symptoms and the corresponding proportions of GP contacts in a large nationwide population based study. More than 9 out of 10 individuals reported having experienced at least one symptom and 37 % had contacted the GP with a symptom. For almost 2/3 of the reported symptoms no gender differences were found concerning the proportion leading to GP contacts.

Declarations

Acknowledgement

This survey is conducted in collaboration between University of Southern Denmark and Aarhus University.

The project is part of the research portfolio at the Research Centre for Cancer Diagnosis in Primary Care (CaP) and is financially supported by the Novo Nordisk Foundation and the Danish Cancer Society.

The authors would like to thank Lise Keller Stark for proofreading the manuscript.

Authors’ Affiliations

(1)
Research Unit of General Practice, Department of Public Health, University of Southern Denmark
(2)
The Research Unit for General Practice, Research Centre for Cancer Diagnosis in Primary Care - CaP, Department of Public Health, Aarhus University

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Copyright

© Elnegaard et al. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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